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Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm

Author

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  • Touqeer Ahmed Jumani

    (School of Electrical Engineering, University Technology Malaysia, Skudai, 81310 Johor Bahru, Malaysia
    Department of Electrical Engineering, Mehran University of Engineering and Technology, SZAB Campus, Khairpur Mirs 66020, Pakistan)

  • Mohd Wazir Mustafa

    (School of Electrical Engineering, University Technology Malaysia, Skudai, 81310 Johor Bahru, Malaysia)

  • Madihah Md Rasid

    (School of Electrical Engineering, University Technology Malaysia, Skudai, 81310 Johor Bahru, Malaysia)

  • Nayyar Hussain Mirjat

    (Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro 76090, Pakistan)

  • Zohaib Hussain Leghari

    (School of Electrical Engineering, University Technology Malaysia, Skudai, 81310 Johor Bahru, Malaysia
    Department of Electrical Engineering, Mehran University of Engineering and Technology, Jamshoro 76090, Pakistan)

  • M. Salman Saeed

    (School of Electrical Engineering, University Technology Malaysia, Skudai, 81310 Johor Bahru, Malaysia
    Department of Power Distribution, Multan Electric Power Company, Multan 66000, Pakistan)

Abstract

Due to the lack of inertia and uncertainty in the selection of optimal Proportional Integral (PI) controller gains, the voltage and frequency variations are higher in the islanded mode of the operation of a Microgrid (MG) compared to the grid-connected mode. This study, as such, develops an optimal control strategy for the voltage and frequency regulation of Photovoltaic (PV) based MG systems operating in islanding mode using Grasshopper Optimization Algorithm (GOA). The intelligence of the GOA is utilized to optimize the PI controller parameters. This ensures an enhanced dynamic response and power quality of the studied MG system during Distributed Generators (DG) insertion and load change conditions. A droop control is also employed within the control architecture, alongside the voltage and current control loops, as a power-sharing controller. In order to validate the performance of the proposed control architecture, its effectiveness in regulating MG voltage, frequency, and power quality is compared with the precedent Artificial Intelligence (AI) based control architectures for the same control objectives. The effectiveness of the proposed GOA based parameter selection method is also validated by analyzing its performance with respect to the improved transient response and power quality of the studied MG system in comparison with that of the Particle Swarm Optimization (PSO) and Whales Optimization Algorithm (WOA) based parameter selection methods. The simulation results establish that the GOA provides a faster and better solution than PSO and WOA which resulted in a minimum voltage and frequency overshoot with minimum output current and Total Harmonic Distortion (THD).

Suggested Citation

  • Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Madihah Md Rasid & Nayyar Hussain Mirjat & Zohaib Hussain Leghari & M. Salman Saeed, 2018. "Optimal Voltage and Frequency Control of an Islanded Microgrid Using Grasshopper Optimization Algorithm," Energies, MDPI, vol. 11(11), pages 1-20, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3191-:d:183579
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    References listed on IDEAS

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    Cited by:

    1. Ghulam Abbas & Aqeel Ahmed Bhutto & Touqeer Ahmed Jumani & Sohrab Mirsaeidi & Mohsin Ali Tunio & Hammad Alnuman & Ahmed Alshahir, 2022. "A Modified Particle Swarm Optimization Algorithm for Power Sharing and Transient Response Improvement of a Grid-Tied Solar PV Based A.C. Microgrid," Energies, MDPI, vol. 16(1), pages 1-14, December.
    2. Marcin Steczek & Włodzimierz Jefimowski & Adam Szeląg, 2020. "Application of Grasshopper Optimization Algorithm for Selective Harmonics Elimination in Low-Frequency Voltage Source Inverter," Energies, MDPI, vol. 13(23), pages 1-16, December.
    3. Giulio Ferro & Michela Robba & Roberto Sacile, 2020. "A Model Predictive Control Strategy for Distribution Grids: Voltage and Frequency Regulation for Islanded Mode Operation," Energies, MDPI, vol. 13(10), pages 1-27, May.
    4. Saleh Masoud Abdallah Altbawi & Ahmad Safawi Bin Mokhtar & Saifulnizam Bin Abdul Khalid & Nusrat Husain & Ashraf Yahya & Syed Aqeel Haider & Rayan Hamza Alsisi & Lubna Moin, 2023. "Optimal Control of a Single-Stage Modular PV-Grid-Driven System Using a Gradient Optimization Algorithm," Energies, MDPI, vol. 16(3), pages 1-23, February.
    5. Amrutha Raju Battula & Sandeep Vuddanti & Surender Reddy Salkuti, 2021. "Review of Energy Management System Approaches in Microgrids," Energies, MDPI, vol. 14(17), pages 1-32, September.
    6. Jun Zhang & Denghua Zhong & Mengqi Zhao & Jia Yu & Fei Lv, 2019. "An Optimization Model for Construction Stage and Zone Plans of Rockfill Dams Based on the Enhanced Whale Optimization Algorithm," Energies, MDPI, vol. 12(3), pages 1-29, February.
    7. Maen Z. Kreishan & Ahmed F. Zobaa, 2021. "Optimal Allocation and Operation of Droop-Controlled Islanded Microgrids: A Review," Energies, MDPI, vol. 14(15), pages 1-45, July.
    8. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    9. Xiang Li & Zhenya Ji & Fengkun Yang & Zhenlan Dou & Chunyan Zhang & Liangliang Chen, 2022. "A Distributed Two-Level Control Strategy for DC Microgrid Considering Safety of Charging Equipment," Energies, MDPI, vol. 15(22), pages 1-20, November.
    10. Seyedamin Valedsaravi & Abdelali El Aroudi & Jose A. Barrado-Rodrigo & Walid Issa & Luis Martínez-Salamero, 2022. "Control Design and Parameter Tuning for Islanded Microgrids by Combining Different Optimization Algorithms," Energies, MDPI, vol. 15(10), pages 1-25, May.
    11. Salman Habib & Ghulam Abbas & Touqeer A. Jumani & Aqeel Ahmed Bhutto & Sohrab Mirsaeidi & Emad M. Ahmed, 2022. "Improved Whale Optimization Algorithm for Transient Response, Robustness, and Stability Enhancement of an Automatic Voltage Regulator System," Energies, MDPI, vol. 15(14), pages 1-18, July.
    12. Talaat, M. & Hatata, A.Y. & Alsayyari, Abdulaziz S. & Alblawi, Adel, 2020. "A smart load management system based on the grasshopper optimization algorithm using the under-frequency load shedding approach," Energy, Elsevier, vol. 190(C).

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